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The purpose of this study is to examine the information needs and seeking behaviors of African refugees in the Midwest United States. The research also investigates the sources participants consulted and their satisfaction with their information seeking and the information found.

This qualitative research study recruited 18 African refugees to participate in one or more data collection modes used in the study (questionnaire, interview, focus group). The data were analyzed using qualitative open, axial and selective coding approaches to identify themes.

The analysis of the data collected provides evidence that refugees had specific information needs centered on housing, health care, employment and education. They were not necessarily satisfied with the information they were able to find. Participants reported initially relying heavily on their caseworkers as sources of information when they first arrived in the United States until they were able to establish larger networks of contacts, which then expanded their information behaviors.

The number of participants and regional focus of the study do not allow for generalization of the findings to all African refugees in the United States. Still, the findings shed light on how to better serve the information needs of African refugees to help them adjust to life in their new environment.

The findings of the study provide guidance for agencies that assist African refugees in adjusting to life in the United States.

This study represents one of the few investigations of the information needs and seeking behaviors of African refugees in the United States.

The purpose of this article is to investigate obesity‐related queries from a public health portal (HealthLink) transaction log.

Multidimensional scaling (MDS) was applied to each of five obesity‐related focus keywords and their co‐occurring terms in submitted queries. After the transaction log data were collected and cleaned, and query terms were extracted and parsed, relationships between a focus keyword and its co‐occurring terms were established. Clustering relationships between focus keywords and their co‐occurring terms were identified and analysed in the MDS visual context.

The MDS analysis produced satisfactory outcomes for all five focus keywords. The term “placements”, in the visual configurations revealed strong grouping tendencies of three to five clusters for each focus keyword.

The findings of this study provide insights into health consumers' internet‐based information‐seeking behaviour on obesity‐related topics. These findings could be used to enhance online search system design and health‐related thesaurus construction.

The purpose of this article is to examine interindexer consistency on a larger scale than other studies have done to determine if group consensus is reached by larger numbers of indexers and what, if any, relationships emerge between assigned terms.

In total, 64 MLIS students were recruited to assign up to five terms to a document. The authors applied basic data modeling and the exploratory statistical techniques of multi‐dimensional scaling (MDS) and hierarchical cluster analysis to determine whether relationships exist in indexing consistency and the coocurrence of assigned terms.

Consistency in the assignment of indexing terms to a document follows an inverse shape, although it is not strictly power law‐based unlike many other social phenomena. The exploratory techniques revealed that groups of terms clustered together. The resulting term cooccurrence relationships were largely syntagmatic.

The results are based on the indexing of one article by non‐expert indexers and are, thus, not generalizable. Based on the study findings, along with the growing popularity of folksonomies and the apparent authority of communally developed information resources, communally developed indexes based on group consensus may have merit.

Consistency in the assignment of indexing terms has been studied primarily on a small scale. Few studies have examined indexing on a larger scale with more than a handful of indexers. Recognition of the differences in indexing assignment has implications for the development of public information systems, especially those that do not use a controlled vocabulary and those tagged by end‐users. In such cases, multiple access points that accommodate the different ways that users interpret content are needed so that searchers may be guided to relevant content despite using different terminology.

This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011–2020. It also examines changes in this structure from 2006–2010 through 2011–2015 to 2016–2020. Results will contribute to a better understanding of the information science research field.

The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011–2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor.

The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011–2015 but shared dominance with information behavior during 2016–2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016–2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011–2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016–2020.

Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

The purpose of this paper is to investigate the significant supply chain issues in the small and medium-sized enterprise (SME) food industry. The objectives are to identify the major themes and the dynamic evolution of SME food supply chain (FSC) issues, the current research trends, the different modelling approaches used in SME FSC, and the most addressed SME food sector.

In all, 3,733 published articles from 2002 to 2018 in the Clarivate Analytics Web of Science database were collected, from which 1,091 articles were shortlisted for the review. The authors used bibliographic coupling combined with co-word analysis to identify the historical relations of the research themes that emerged during the periods 2002–2014 and 2002–2018.

This research identified five major research themes such as production and distribution in alternative food networks, relationship, safety and standards in the FSC, greenhouse gas (GHG) emission impact of the farm food system, traceability and product quality in FSC and asymmetric price transmission in the FSC. Among the identified themes, GHG emission impact of the farm food system and traceability and product quality in the FSC have received increasing attention in recent years. The dairy sector is the most addressed sector (36 per cent), followed by fruits and vegetables (27 per cent), meat and poultry (18 per cent), seafood (10 per cent) and grains and oilseed (8 per cent). It is also identified that the dairy sector has received significant attention in the “GHG Emission impact of farm food system” theme. Similarly, meat and poultry sectors have received much attention in the “Traceability and product quality in the food supply chain” theme. Also, the authors identified that the empirical modelling approaches are the most commonly used solution methodology, followed by the conceptual/qualitative methods in the SME FSC.

This study maps and summarizes the existing knowledge base of supply chain issues in the SME food sector. The results of this review provide the major research areas, most commonly used approaches and food sectors addressed. This study also highlights the research gaps and potential future research direction.